Certificate in AI Algorithms: Efficient Evaluation
-- ViewingNowThe Certificate in AI Algorithms: Efficient Evaluation is a comprehensive course designed to equip learners with essential skills in AI algorithms and their efficient evaluation. This course emphasizes the importance of selecting and applying appropriate algorithms for various AI tasks, as well as the critical role of efficient evaluation in ensuring the success of AI projects.
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⢠Unit 1: Introduction to AI Algorithms
⢠Unit 2: Types of AI Algorithms: Supervised, Unsupervised, and Reinforcement Learning
⢠Unit 3: Evaluation Metrics for AI Algorithms: Accuracy, Precision, Recall, F1 Score, ROC Curve
⢠Unit 4: Optimization Techniques for AI Algorithms: Gradient Descent, Stochastic Gradient Descent, Adam Optimizer
⢠Unit 5: Regularization Techniques for AI Algorithms: L1 and L2 Regularization, Dropout
⢠Unit 6: Bias-Variance Tradeoff in AI Algorithms
⢠Unit 7: Ensemble Methods for AI Algorithms: Bagging, Boosting, Random Forests
⢠Unit 8: Hyperparameter Tuning for AI Algorithms: Grid Search, Random Search, Bayesian Optimization
⢠Unit 9: Deep Learning Algorithms: Convolutional Neural Networks, Recurrent Neural Networks, Transformers
⢠Unit 10: Ethical Considerations in AI Algorithms: Bias, Fairness, and Transparency
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